派生自 ruleprocess
main.go
@@ -4,6 +4,12 @@ "basic.com/dbapi.git" "basic.com/pubsub/protomsg.git" "basic.com/valib/deliver.git" "net/http" _ "net/http/pprof" "ruleprocess/insertdata" "ruleprocess/util" "time" //"bufio" //"bytes" "flag" @@ -18,12 +24,14 @@ "ruleprocess/ruleserver" "sync" ) var dbIp = flag.String("dbIp","127.0.0.1","dbserver ip") var dbPort = flag.Int("dbPort",8001,"default dbPort=8001") var surveyPort = flag.Int("surveyPort",40007,"survey port") //心跳 var pubPort = flag.Int("pubPort",50007,"pubsub port") //数据更新 var dbIp = flag.String("dbIp", "127.0.0.1", "dbserver ip") var dbPort = flag.Int("dbPort", 8001, "default dbPort=8001") var surveyPort = flag.Int("surveyPort", 40007, "survey port") //心跳 var pubPort = flag.Int("pubPort", 50007, "pubsub port") //数据更新 var initchan = make(chan bool) func init () { func init() { // 日志初始化 logger.Config("./info.log", logger.DebugLevel) logger.Info("日志初始化成功！") @@ -32,14 +40,17 @@ func main() { flag.Parse() wg := sync.WaitGroup{} wg.Add(2) wg.Add(3) dbapi.Init(*dbIp,*dbPort) go cache.Init(initchan,*dbIp,*surveyPort,*pubPort) logger.Info("cache init completed!!!",<- initchan)//dbserver初始化完毕 dbapi.Init(*dbIp, *dbPort) go cache.Init(initchan, *dbIp, *surveyPort, *pubPort) logger.Info("cache init completed!!!", <-initchan) //dbserver初始化完毕 //fmt.Println("缓存初始化完成",<- initchan)//dbserver初始化完毕 ruleserver.Init() go ruleserver.TimeTicker() go func() { http.ListenAndServe("0:0:0:0:8069",nil) }() go ruleserver.StartServer() nReciever("ipc:///tmp/sdk-2-rules-process.ipc", deliver.PushPull, 1) wg.Wait() @@ -53,32 +64,43 @@ var msg []byte var err error //msgChan := make(chan []byte,100) for { select { // case <-ctx.Done(): // return default: msg, err = c.Recv() //msgChan <- msg if err != nil { logger.Info("recv error : ", err) fmt.Println("recv error : ", err) continue } else { arg := ruleserver.SdkDatas{} paramFormat(msg, &arg) //m := paramFormat(msg, &arg) //logger.Info("解析出来的数据：", arg) //ruleserver.Judge(&arg,&m) // 把sdkMessage传进去，方便缓存数据时拼出一个resultMag //// 把arg里的打的标签拿出来给m再封装一层 //resultMag := ruleserver.ResultMsg{SdkMessage: &m, RuleResult: arg.RuleResult} ////logger.Info("打完标签后的结果：",resultMag) //// 将打完标签的数据插入到ES //insertdata.InsertToEs(resultMag) //runtime.GOMAXPROCS(runtime.NumCPU()) //logger.Debug("使用的cpu个数：",runtime.NumCPU()) //go func(msg []byte) { logger.Debug("当前时间戳：", time.Now().Unix()) arg := ruleserver.SdkDatas{} //paramFormat(msg, &arg) start := time.Now() m := paramFormat(msg, &arg) // 进行规则处理判断(打上规则的标签) ruleserver.Judge(&arg, &m) // 把sdkMessage传进去，方便缓存数据时拼出一个resultMag // 把arg里的打的标签拿出来给m再封装一层 resultMsg := ruleserver.ResultMsg{SdkMessage: &m, RuleResult: arg.RuleResult} logger.Debug("规则判断完所用时间：", time.Since(start)) // 将打完标签的数据插入到ES insertdata.InsertToEs(resultMsg) logger.Debug("插入完Es所用时间：", time.Since(start)) //事件推送 //go labelFilter.Judge(resultMsg) //}(msg) } } } } // 将外部传进来的rect（top,bottom,left,right）转化为自己内部的rect(left top width height) func rectFormat(rcobj *protomsg.Rect) ruleserver.Rect { @@ -106,105 +128,95 @@ panic("解析msg时出现错误") } // 找201的人脸数据 for _, sdkinfo := range m.Tasklab.Sdkinfos { if sdkinfo.Sdktype == "FaceDetect" && m.Cid == "e7e3f5b0-d0ef-40af-a9c9-eefd736937bf"{ // 人脸检测 // 先进行一下追踪 ruleserver.FaceIsSame(&m) args.CameraId = m.Cid args.TaskId = m.Tasklab.Taskid // 把图片的二进制解压缩进行画框在压缩回去 bdata, err := util.UnCompress(m.Data) if err != nil { panic("解压缩图片时出现错误") } i := protomsg.Image{} err = proto.Unmarshal(bdata, &i) logger.Info("接到数据，摄像机为：", m.Cid, "图片的id为：", i.Id) //logger.Info("----------------看看有几个算法：",len(m.Tasklab.Sdkinfos)) for _, sdkinfo := range m.Tasklab.Sdkinfos { // yolo算法 if sdkinfo.Sdktype == "Yolo" { arg := ruleserver.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = true //bdata, err := util.UnCompress(m.Data) //if err != nil { // panic("解压缩图片时出现错误") //} //i := protomsg.Image{} //err = proto.Unmarshal(bdata, &i) arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) // 暂时写死，sdk还没有这俩算法 arg.KeepRight = false arg.IsStatic = false logger.Info("-----追踪之后sdkinfo.Sdkdata的长度为：----", len(sdkinfo.Sdkdata)) if len(sdkinfo.Sdkdata) > 1 { logger.Debug("有201的人脸数据了") // 大于1才有数据 yoloParam := protomsg.ParamYoloObj{} err = proto.Unmarshal(sdkinfo.Sdkdata, &yoloParam) if err != nil { logger.Info("解析YOLO sdk数据时出现错误", err) continue } var yoloNum int = 0 for _, info := range yoloParam.Infos { if info.Typ == 0 { //logger.Debug("-------------yolo的坐标有几个",info.RcObj) photoMap := ruleserver.PhotoMap{Rects: rectFormat(info.RcObj), Score: float64(info.Prob) * 100, IsYolo: true} arg.Photo = append(arg.Photo, photoMap) yoloNum++ } } logger.Info("--------------追踪之后yolo的个数：", yoloNum) args.Sdkdata = append(args.Sdkdata, &arg) } else { logger.Debug("没有201的人脸数据") continue } } if sdkinfo.Sdktype == "FaceDetect" { // 人脸检测 arg := ruleserver.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false //bdata, err := util.UnCompress(m.Data) //if err != nil { // panic("解压缩图片时出现错误") //} //i := protomsg.Image{} //err = proto.Unmarshal(bdata, &i) arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) // 暂时写死，sdk还没有这俩算法 arg.KeepRight = false arg.IsStatic = false if len(sdkinfo.Sdkdata) > 1 { faceParam := protomsg.ParamFacePos{} err = proto.Unmarshal(sdkinfo.Sdkdata, &faceParam) if err != nil { logger.Info("解析FACE sdk数据时出现错误", err) continue } logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces)) for _, info := range faceParam.Faces { //logger.Info("_______________________________________________第一次看相似值：",info.Pos.FAngle.Confidence*100) photoMap := ruleserver.PhotoMap{Id: info.Pos.FaceID, Rects: rectFormat(info.Pos.RcFace), Score: float64(info.Pos.FAngle.Confidence * 100), IsYolo: false, ThftRes: *(info.Result), Feature: info.Feats} arg.Photo = append(arg.Photo, photoMap) } args.Sdkdata = append(args.Sdkdata, &arg) } else { continue } } } // 先进行一下追踪 //ruleserver.FaceIsSame(&m) //args.CameraId = m.Cid //args.TaskId = m.Tasklab.Taskid //// 把图片的二进制解压缩进行画框在压缩回去 //bdata, err := util.UnCompress(m.Data) //if err != nil { // panic("解压缩图片时出现错误") //} //i := protomsg.Image{} //err = proto.Unmarshal(bdata, &i) ////logger.Info("----------------看看有几个算法：",len(m.Tasklab.Sdkinfos)) //for _, sdkinfo := range m.Tasklab.Sdkinfos { // yolo算法 // if sdkinfo.Sdktype == "Yolo" { // arg := ruleserver.SdkData{} // arg.TaskId = m.Tasklab.Taskid // arg.IpcId = sdkinfo.Ipcid // arg.IsYolo = true // bdata, err := util.UnCompress(m.Data) // if err != nil { // panic("解压缩图片时出现错误") // } // i := protomsg.Image{} // err = proto.Unmarshal(bdata, &i) // arg.ImageWidth = int(i.Width) // arg.ImageHeight = int(i.Height) // // 暂时写死，sdk还没有这俩算法 // arg.KeepRight = false // arg.IsStatic = false // logger.Info("-----追踪之后sdkinfo.Sdkdata的长度为：----",len(sdkinfo.Sdkdata)) // if len(sdkinfo.Sdkdata) > 1 { // // 大于1才有数据 // yoloParam := protomsg.ParamYoloObj{} // err = proto.Unmarshal(sdkinfo.Sdkdata, &yoloParam) // if err != nil { // logger.Info("解析YOLO sdk数据时出现错误", err) // continue // } // var yoloNum int = 0 // for _, info := range yoloParam.Infos { // if info.Typ == 0 { // //logger.Debug("-------------yolo的坐标有几个",info.RcObj) // photoMap := ruleserver.PhotoMap{Rects: rectFormat(info.RcObj), Score: float64(info.Prob)*100,IsYolo:true} // arg.Photo = append(arg.Photo, photoMap) // yoloNum++ // } // } // logger.Info("--------------追踪之后yolo的个数：",yoloNum) // args.Sdkdata = append(args.Sdkdata,&arg) // } else { // continue // } // // } // if sdkinfo.Sdktype == "FaceDetect" { // 人脸检测 // arg := ruleserver.SdkData{} // arg.TaskId = m.Tasklab.Taskid // arg.IpcId = sdkinfo.Ipcid // arg.IsYolo = false // bdata, err := util.UnCompress(m.Data) // if err != nil { // panic("解压缩图片时出现错误") // } // i := protomsg.Image{} // err = proto.Unmarshal(bdata, &i) // arg.ImageWidth = int(i.Width) // arg.ImageHeight = int(i.Height) // // 暂时写死，sdk还没有这俩算法 // arg.KeepRight = false // arg.IsStatic = false // if len(sdkinfo.Sdkdata) > 1 { // faceParam := protomsg.ParamFacePos{} // err = proto.Unmarshal(sdkinfo.Sdkdata, &faceParam) // if err != nil { // logger.Info("解析FACE sdk数据时出现错误", err) // continue // } // logger.Info("--------------追踪之后yolo的个数：",len(faceParam.Faces)) // for _, info := range faceParam.Faces { // //logger.Info("_______________________________________________第一次看相似值：",info.Pos.FAngle.Confidence*100) // photoMap := ruleserver.PhotoMap{Rects: rectFormat(info.Pos.RcFace), Score: float64(info.Pos.FAngle.Confidence*100), IsYolo:false,ThftRes:*(info.Result),Feature:info.Feats} // arg.Photo = append(arg.Photo, photoMap) // } // args.Sdkdata = append(args.Sdkdata,&arg) // } else { // continue // } // } //} return m } }
